Degenerative Cervical Myelopathy: A Practical Approach to Diagnosis

Evidence-based commentary on the diagnosis, management, and further research of degenerative cervical spinal cord compression in the absence of clinical symptoms of myelopathy

Degenerative cervical myelopathy (DCM) represents the final consequence of a series of degenerative changes in the cervical spine, resulting in cervical spinal canal stenosis and mechanical stress on the cervical spinal cord. This process leads to subsequent pathophysiological processes in the spinal cord tissues. The primary mechanism of injury is degenerative compression of the cervical spinal cord, detectable by magnetic resonance imaging (MRI), serving as a hallmark for diagnosing DCM. However, the relative resilience of the cervical spinal cord to mechanical compression leads to clinical-radiological discordance, i.e., some individuals may exhibit MRI findings of DCC without the clinical signs and symptoms of myelopathy. This degenerative compression of the cervical spinal cord without clinical signs of myelopathy, potentially serving as a precursor to the development of DCM, remains a somewhat controversial topic. In this review article, we elaborate on and provide commentary on the terminology, epidemiology, natural course, diagnosis, predictive value, risks, and practical management of this condition-all of which are subjects of ongoing debate.

The value of Clinical signs in the diagnosis of Degenerative Cervical Myelopathy - A Systematic review and Meta-analysis

STUDY DESIGN

Delayed diagnosis of degenerative cervical myelopathy (DCM) is likely due to a combination of its subtle symptoms, incomplete neurological assessments by clinicians and a lack of public and professional awareness. Diagnostic criteria for DCM will likely facilitate earlier referral for definitive management.

OBJECTIVES

This systematic review aims to determine (i) the diagnostic accuracy of various clinical signs and (ii) the association between clinical signs and disease severity in DCM?

METHODS

A search was performed to identify studies on adult patients that evaluated the diagnostic accuracy of a clinical sign used for diagnosing DCM. Studies were also included if they assessed the association between the presence of a clinical sign and disease severity. The QUADAS-2 tool was used to evaluate the risk of bias of individual studies.

RESULTS

This review identified eleven studies that used a control group to evaluate the diagnostic accuracy of various signs. An additional 61 articles reported on the frequency of clinical signs in a cohort of DCM patients. The most sensitive clinical tests for diagnosing DCM were the Tromner and hyperreflexia, whereas the most specific tests were the Babinski, Tromner, clonus and inverted supinator sign. Five studies evaluated the association between the presence of various clinical signs and disease severity. There was no definite association between Hoffmann sign, Babinski sign or hyperreflexia and disease severity.

CONCLUSION

The presence of clinical signs suggesting spinal cord compression should encourage health care professionals to pursue further investigation, such as neuroimaging to either confirm or refute a diagnosis of DCM.

The Frequency of Symptoms in Patients With a Diagnosis of Degenerative Cervical Myelopathy: Results of a Scoping Review

STUDY DESIGN

Delayed diagnosis of degenerative cervical myelopathy (DCM) is associated with reduced quality of life and greater disability. Developing diagnostic criteria for DCM has been identified as a top research priority.

OBJECTIVES

This scoping review aims to address the following questions: What is the diagnostic accuracy and frequency of clinical symptoms in patients with DCM?

METHODS

A scoping review was conducted using a database of all primary DCM studies published between 2005 and 2020. Studies were included if they (i) assessed the diagnostic accuracy of a symptom using an appropriate control group or (ii) reported the frequency of a symptom in a cohort of DCM patients.

RESULTS

This review identified three studies that discussed the diagnostic accuracy of various symptoms and included a control group. An additional 58 reported on the frequency of symptoms in a cohort of patients with DCM. The most frequent and sensitive symptoms in DCM include unspecified paresthesias (86%), hand numbness (82%) and hand paresthesias (79%). Neck and/or shoulder pain was present in 51% of patients with DCM, whereas a minority had back (19%) or lower extremity pain (10%). Bladder dysfunction was uncommon (38%) although more frequent than bowel (23%) and sexual impairment (4%). Gait impairment is also commonly seen in patients with DCM (72%).

CONCLUSION

Patients with DCM present with many different symptoms, most commonly sensorimotor impairment of the upper extremities, pain, bladder dysfunction and gait disturbance. If patients present with a combination of these symptoms, further neuroimaging is indicated to confirm the diagnosis of DCM.

Is Upper Extremity or Lower Extremity Function More Important for Patient Satisfaction? An Analysis of 24-Month Outcomes from the QOD Cervical Spondylotic Myelopathy Cohort

STUDY DESIGN

Retrospective analysis of a prospective, multicenter registry.

OBJECTIVE

To assess whether upper or lower limb mJOA improvement more strongly associates with patient satisfaction after surgery for cervical spondylotic myelopathy (CSM).

SUMMARY OF BACKGROUND DATA

The modified Japanese Orthopaedic Association (mJOA) is commonly used to assess functional status in patients with CSM. Patients present with upper and/or lower extremity dysfunction, and it is unclear whether improvement in one and/or both symptoms drives postoperative patient satisfaction.

METHODS

This study utilizes the prospective Quality Outcomes Database (QOD) CSM data set. Clinical outcomes included mJOA and North American Spine Society (NASS) satisfaction. The upper limb mJOA score was defined as upper motor plus sensory mJOA, and the lower limb mJOA as lower motor plus sensory mJOA. Ordered logistic regression was used to determine whether upper or lower limb mJOA was more closely associated with NASS satisfaction, adjusting for other covariates.

RESULTS

Overall, 1141 patients were enrolled in the QOD CSM cohort. In all, 780 had both preoperative and 24-month mJOA scores, met inclusion criteria, and were included for analysis. The baseline mJOA was 12.1±2.7, and postoperatively, 85.6% would undergo surgery again (NASS 1 or 2, satisfied). Patients exhibited mean improvement in both upper (baseline:3.9±1.4 vs. 24 mo:5.0±1.1, P<0.001) and lower limb mJOA (baseline:3.9±1.4 vs. 24 mon:4.5±1.5, P<0.001); however, the 24-month change in the upper limb mJOA was greater (upper:1.1±1.6 vs. lower:0.6±1.6, P<0.001). Across 24-month NASS satisfaction, the baseline upper and lower limb mJOA scores were similar (pupper=0.28, plower=0.092). However, as satisfaction decreased, the 24-month change in upper and lower limb mJOA decreased as well (pupper<0.001, plower<0.001). Patients with NASS scores of 4 (lowest satisfaction) did not demonstrate significant differences from baseline in upper or lower limb mJOA (P>0.05). In ordered logistic regression, NASS satisfaction was independently associated with upper limb mJOA improvement (OR=0.81; 95% CI: 0.68-0.97; P=0.019) but not lower limb mJOA improvement (OR=0.84; 95% CI: 0.70-1.0; P=0.054).

CONCLUSIONS

As the magnitude of upper and lower mJOA improvement decreased postoperatively, so too did patient satisfaction with surgical intervention. Upper limb mJOA improvement was a significant independent predictor of patient satisfaction, whereas lower limb mJOA improvement was not. These findings may aid preoperative counseling, stratified by patients' upper and lower extremity treatment expectations.

LEVEL OF EVIDENCE

Level-III.

Impaired communication at the neuromotor axis during Degenerative Cervical Myelopathy

Degenerative Cervical Myelopathy (DCM) is a progressive neurological condition characterized by structural alterations in the cervical spine, resulting in compression of the spinal cord. While clinical manifestations of DCM are well-documented, numerous unanswered questions persist at the molecular and cellular levels. In this study, we sought to investigate the neuromotor axis during DCM. We use a clinically relevant mouse model, where after 3 months of DCM induction, the sensorimotor tests revealed a significant reduction in both locomotor activity and muscle strength compared to the control group. Immunohistochemical analyses showed alterations in the gross anatomy of the cervical spinal cord segment after DCM. These changes were concomitant with the loss of motoneurons and a decrease in the number of excitatory synaptic inputs within the spinal cord. Additionally, the DCM group exhibited a reduction in the endplate surface, which correlated with diminished presynaptic axon endings in the supraspinous muscles. Furthermore, the biceps brachii (BB) muscle exhibited signs of atrophy and impaired regenerative capacity, which inversely correlated with the transversal area of remnants of muscle fibers. Additionally, metabolic assessments in BB muscle indicated an increased proportion of oxidative skeletal muscle fibers. In line with the link between neuromotor disorders and gut alterations, DCM mice displayed smaller mucin granules in the mucosa layer without damage to the epithelial barrier in the colon. Notably, a shift in the abundance of microbiota phylum profiles reveals an elevated Firmicutes-to-Bacteroidetes ratio-a consistent hallmark of dysbiosis that correlates with alterations in gut microbiota-derived metabolites. Additionally, treatment with short-chain fatty acids stimulated the differentiation of the motoneuron-like NSC34 cell line. These findings shed light on the multifaceted nature of DCM, resembling a synaptopathy that disrupts cellular communication within the neuromotor axis while concurrently exerting influence on other systems. Notably, the colon emerges as a focal point, experiencing substantial perturbations in both mucosal barrier integrity and the delicate balance of intestinal microbiota.

Deep Learning Algorithm for Identifying Cervical Cord Compression Due to Degenerative Canal Stenosis on Radiography

STUDY DESIGN

Cross-sectional study.

OBJECTIVE

Validate the diagnostic accuracy of a deep-learning algorithm for cervical cord compression due to degenerative canal stenosis on radiography.

SUMMARY OF BACKGROUND DATA

The diagnosis of degenerative cervical myelopathy is often delayed, resulting in improper management. Screening tools for suspected degenerative cervical myelopathy would help identify patients who require detailed physical evaluation.

MATERIALS AND METHODS

Data from 240 patients (120 with cervical stenosis on magnetic resonance imaging and 120 age and sex-matched controls) were randomly divided into training (n = 198) and test (n = 42) data sets. The deep-learning algorithm, designed to identify the suspected stenosis level on radiography, was constructed using a convolutional neural network model called EfficientNetB2, and radiography and magnetic resonance imaging data from the training data set. The accuracy and area under the curve of the receiver operating characteristic curve were calculated for the independent test data set. Finally, the number of correct diagnoses was compared between the algorithm and 10 physicians using the test cohort.

RESULTS

The diagnostic accuracy and area under the curve of the deep-learning algorithm were 0.81 and 0.81, respectively, in the independent test data set. The rate of correct responses in the test data set was significantly higher for the algorithm than for the physician's consensus (81.0% vs . 66.2%; P = 0.034). Furthermore, the accuracy of the algorithm was greater than that of each individual physician.

CONCLUSIONS

We developed a deep-learning algorithm capable of suggesting the presence of cervical spinal cord compression on cervical radiography and highlighting the suspected levels on radiographic imaging when cord compression is identified. The diagnostic accuracy of the algorithm was greater than that of spine physicians.

LEVEL OF EVIDENCE

Level IV.

Screening for degenerative cervical myelopathy with the 10-second grip-and-release test using a smartphone and machine learning: A pilot study

Objective

Early detection and intervention are essential for the mitigation of degenerative cervical myelopathy (DCM). However, although several screening methods exist, they are difficult to understand for community-dwelling people, and the equipment required to set up the test environment is expensive. This study investigated the viability of a DCM-screening method based on the 10-second grip-and-release test using a machine learning algorithm and a smartphone equipped with a camera to facilitate a simple screening system.

Methods

Twenty-two participants comprising a group of DCM patients and 17 comprising a control group participated in this study. A spine surgeon diagnosed the presence of DCM. Patients performing the 10-second grip-and-release test were filmed, and the videos were analyzed. The probability of the presence of DCM was estimated using a support vector machine algorithm, and sensitivity, specificity, and area under the curve (AUC) were calculated. Two assessments of the correlation between estimated scores were conducted. The first used a random forest regression model and the Japanese Orthopaedic Association scores for cervical myelopathy (C-JOA). The second assessment used a different model, random forest regression, and the Disabilities of the Arm, Shoulder, and Hand (DASH) questionnaire.

Results

The final classification model had a sensitivity of 90.9%, specificity of 88.2%, and AUC of 0.93. The correlations between each estimated score and the C-JOA and DASH scores were 0.79 and 0.67, respectively.

Conclusions

The proposed model could be a helpful screening tool for DCM as it showed excellent performance and high usability for community-dwelling people and non-spine surgeons.

Development and testing of a new application for measuring motion at the cervical spine

Background

Cervical myelopathy is a progressive disease, and early detection and treatment contribute to prognosis. Evaluation of cervical intervertebral instability by simple X-ray is used in clinical setting and the information about instability is important to understand the cause of myelopathy, but evaluation of the intervertebral instability by X-ray is complicated. To reduce the burden of clinicians, a system that automatically measures the range of motion was developed by comparing the flexed and extended positions in the lateral view of a simple X-ray of the cervical spine. The accuracy of the system was verified by comparison with spine surgeons and residents to determine whether the system could withstand actual use.

Methods

An algorithm was created to recognize the four corners of the vertebral bodies in a lateral cervical spine X-ray image, and a system was constructed to automatically measure the range of motion between each vertebra by comparing X-ray images of the cervical spine in extension and flexion. Two experienced spine surgeons and two residents performed the study on the remaining 23 cases. Cervical spine range of motion was measured manually on X-ray images and compared with automatic measurement by this system.

Results

Of a total of 322 cervical vertebrae in 46 images, 313 (97%) were successfully estimated by our learning model. The mean intersection over union value for all the 46-test data was 0.85. The results of measuring the CRoM angle with the proposed cervical spine motion angle measurement system showed that the mean error from the true value was 3.5° and the standard deviation was 2.8°. The average standard deviations for each measurement by specialist and residents are 2.9° and 3.2°.

Conclusions

A system for measuring cervical spine range of motion on X-ray images was constructed and showed accuracy comparable to that of spine surgeons. This system will be effective in reducing the burden on and saving time of orthopedic surgeons by avoiding manually measuring X-ray images.

Trial registration Retrospectively registered with opt-out agreement.